Summary and conclusions

Comparative health workforce analysis is meaningful only when the available information is based on com-mon definition and classification of health workers.

There is no single operational boundary of what con-stitutes the health workforce. Many assessments use country-specific or even tool-specific definitions and titles that are not always comparable across countries or over time. However, a growing number of coun-tries are disseminating health labour data that can be mapped to international standard classifications – such as the International Standard Classification of Education, the International Standard Classification of Occupations, and the International Standard Industrial Classification of All Economic Activities. These classifi-cations provide a coherent framework for categorizing key workforce variables (vocational training, occupation and industry of employment, respectively) according to shared characteristics. Using this trichotomy allows the identification of people with training in health, of people employed in health-related occupations, and of people employed in health services industries.

Health workforce analyses can draw on data from a number of sources, including standard statistical sources outside the (traditional) health sector. Selected tools for guiding the collection and coding of statisti-cal information on economic activity from population censuses and surveys can be found online at the hand-books, guidelines and training manuals section of the United Nations Statistics Division web site (17) (see also 18, 19). The United Nations Statistics Division (20) recommends the collection and processing of census data on education, occupation and industry catego-rized in accordance with, or in a manner convertible to, the latest revision available of the relevant international classification (i.e. ISCED, ISCO and ISIC, respec-tively). It is further recommended that countries code the collected responses at the lowest possible level of classification detail supported by the information given.

In particular, in order to facilitate detailed and accurate coding for occupation data, the questionnaire should

ask each active person for both the occupational title and a brief description of the main tasks and duties performed on the job. It is expected that possibilities for health workforce analyses will be strengthened in the current global series of censuses, known as the 2010 round (covering the period 2005 to 2014), which will largely be able to exploit the new ISCO-08 revision.

For some countries, human resources for health anal-yses based on population census and survey data can be facilitated through collaborative research projects aiming to harmonize microdata variables and structures for public use. Key microdata provid-ers include the Integrated Public Use Microdata Series (21), the African Census Analysis Project (22) and the Luxembourg Income Study (23). Such projects pro-cess census and survey microdata series for multiple countries – with education, occupation and indus-try variables mapped where possible to ISCED, ISCO and ISIC, respectively – and help disseminate the rele-vant documentation for scholarly and policy research.

Chapter 8 of this Handbook presents a multicountry analysis of health workforce statistics making use of the Integrated Public Use Microdata Series (21). The analy-sis draws on available occupational data from the 2000 round of censuses mapped to ISCO-88.

Even with ongoing improvement and revisions, given their nature, standardized classifications are inherently generalized and attempt to simplify a very complex system for statistical purposes. They may not always capture the full complexity and dynamics of the health labour market. The World Health Organization, International Labour Organization and other partners are continually engaged in initiatives to improve inter-national classifications relevant for health workforce analysis and promote their use. This includes ongoing enumeration of the various sources of data and types of classifications used for monitoring health workers (7). This may facilitate definitional harmonization of the health workforce within and across countries, and be used to develop a road map on how to improve health workforce classifications at the national and interna-tional levels. Such exercises continue to benefit from exchanges and interactions among those that produce and use this information from diverse perspectives, including national governments (ministries of health, labour and education, and central statistical offices), health professional associations, WHO regional and country offices, other international bodies with health and statistical interests, nongovernmental and private organizations working in health and statistics, and aca-demic and research institutions.

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Part II:

MONITORING THE STAGES OF THE

WORKING LIFESPAN

Monitoring the active health

workforce: indicators, data sources and illustrative analysis

FELIX RIGOLI, BOB POND, NEERU GUPTA, CHRISTOPHER H HERBST

3.1 Introduction

Human resources for health (HRH) have long been recognized as “the cornerstone of the [health] sec-tor to produce, deliver, and manage services” (1).

Assessments of HRH are required for various pur-poses, notably for planning, implementing, monitoring and evaluating health sector strategies, programmes and interventions. The importance of sound empir-ical evidence for informed policy decision-making and monitoring of progress in strengthening health workforce development and management is widely recognized. Precisely describing HRH can help to identify opportunities and constraints for scaling up health interventions.

The size and distribution of the health workforce is the result of the inflow into, outflow from and circu-lation of workers between, for example, different sectors (public or private), industries (health services or other), regions (rural or urban), countries and sta-tuses (employed, unemployed or inactive) (Figure 3.1).

Various permutations and combinations of what consti-tutes the health workforce potentially exist, depending on each country’s situation and the means of monitor-ing. A framework for harmonizing the boundaries and constituency of the health workforce across contexts is presented in Chapter 2 of this Handbook. To facilitate data collection and analysis processes, it is important to focus on a limited and essential number of indica-tors that are comparable and measurable regularly using standard data sources (2). Such data sources include population-based sources (censuses and sur-veys), health facility assessments and administrative records. For specialized or in-depth HRH assessments, information can further be drawn from, for example, pro-fessional registries, national health accounts, records of health education and training institutes, and qualita-tive studies.

The development of a comprehensive evidence base generally requires combining different types of infor-mation that may exist, frequently scattered across different sources. This chapter focuses on describing

3

Figure 3.1 Stocks and flows of the health workforce

Pre-entry to labour force Training in

health-related field

Training in non-health field

No formal training

Migration Health sector

Non-health sector

Unemployed Health-related

tasks

Non-health-related tasks Rural

Public Salaried Full time Patient care

Urban Private Self-employed Part time Administrative or other tasks

Retirement

Work-limiting disability of death

Other reasons (e.g. family care) Labour force activity

Exit from labour force

the tools and means to monitor the active health work-force, that is, all people currently participating in the health labour market. Core indicators for characterizing HRH are first identified, with an emphasis on optimiz-ing comparability across countries and over time. Key potential sources of data are then reviewed; both pri-mary sources and standard statistical sources are examined, and the opportunities and challenges they offer for health workforce analysis are considered.

Illustrative examples are presented, using case stud-ies from various countrstud-ies and sources. Lastly, some lessons learnt and recommendations for strengthening HRH information and monitoring systems within coun-tries are discussed. The present chapter is primarily devoted to monitoring current health workforce activity;

measurements of entry (notably, pre-service education and training) and exit (attrition due to various factors, including migration, retirement and death) are the focus of the next two chapters in this Handbook, respectively.

3.2 Core indicators for HRH analysis: what needs to be monitored?

Effective monitoring and evaluation of HRH in coun-tries requires agreement upon a core set of indicators at the subnational, national and international levels to inform decision-making among national authorities and other stakeholders. Ideally, the indicators retained should be characterized by “SMART” properties: spe-cific (measures exactly the result); measurable (so that the result can be tracked); attainable (so that the result can be compared against a realistic target); rele-vant (to the intended result); and timebound (indicates a specific time period). The ongoing and consistent measurement of these indicators allows monitoring of how HRH-related programmes and policies are being implemented. Once the baseline data have been gen-erated, an evaluation framework can be established with periodic targets for analysis in terms of change and progress over time, that is, whether activities have been implemented in the right direction in accordance with the original plans and strategic objectives.

Table 3.1 presents a series of indicators that, when sys-tematically measured, can be used to track the active health workforce (2, 3). At the most basic, there is a need to know how many people are working in the field of health, their characteristics and distribution. In con-sidering the size of a country’s health workforce at a given moment, or measuring the stock of health work-ers, it is crucial to distinguish whether the snapshot includes workers employed at health-care facilities (differentiating between those on facility duty rosters versus those physically headcounted on the day of

the assessment), persons having been educated in a health-related field regardless of place of employment, or persons having been educated in a health-related field regardless of current labour force status.

Measuring the skills mix of the health workforce offers a means to assess the combination of categories of personnel at a specific time and identify possible imbalances related to a disparity in the numbers of vari-ous health occupations. Statistics on skills mix can help inform strategies to ensure the most appropriate and cost-effective combination of roles and staff. Because counts of workers in the private sector are likely to be less accurate when drawing on administrative data sources than counts of those in the public sector, and because private for-profit providers are often less accessible to low-income populations, it is also rec-ommended that indicators be used to monitor workers’

employment sector (public, private for-profit or private not-for-profit).

As detailed in the previous chapter, comprehensive assessments require accurate information on occupa-tion, industry and training. Drawing upon a combination of these types of information will enable the identi-fication of, for example, employment in non-health activities among those with a health-related educa-tion, and employment in health activities with jobs that do not require clinical skills (see Chapter 2). Additional indicators on labour productivity, unemployment and underemployment, and emigration, for instance, will allow monitoring of workforce wastage, or excess loss in utility due to attrition or poor productivity that could have been prevented or managed (4). Health workforce metrics, or measurements of particular characteris-tics of performance or efficiency of HRH development strategies, can further be assessed by means of indi-cators on HRH renewal and migration (2).

Comparability of HRH statistics across countries and over time can be enhanced through the setting and use of common definitions and classifications for mon-itoring the labour market. This includes the collection, processing and dissemination of data following inter-nationally standardized classifications, including the International Standard Classification of Occupations (ISCO), the International Standard Industrial Classification of All Economic Activities (ISIC), the International Standard Classification of Education (ISCED) and the International Classification of Status in Employment (ICSE).

Depending on the data source used, indicators on HRH may be disaggregated by selected character-istics for further analysis. Disaggregation of relevant indicators allows for monitoring progress in health

Monitoring the active health workforce: indicators, data sources and illustrative analysis

worker training, recruitment and management policies among underserved communities or other nationally prioritized population groups. Disaggregating infor-mation on earned income among health workers by sex, for example, can be useful for monitoring gen-der gap in occupational earnings. Stratification of workforce statistics by district, province or region is particularly important for monitoring equity of geo-graphical access to health services. HRH renewal can be indirectly assessed through the age distribu-tion of the active health workforce, notably in terms of the ratio of younger workers (under 30 years) to those close to retirement age.Depending on the nature of the indicator and the data source, an evaluation of HRH programmes and policies can be carried out in the short, medium or longer terms. For example, certain aspects of HRH dynamics are only likely to change to a significant degree over the long term, such as the production of physicians over at least a decade or so, given the lengthy pre-service training requirements for this category of health workers.

3.3 Overview of potential data sources

Policies and programmes for the health sector should be informed by timely, reliable and valid data. Despite a prevailing view that statistics on the health workforce are scarce, diverse sources that can potentially pro-duce relevant information exist even in low-income countries, including population censuses and sur-veys, facility assessments and routine administrative records. There are strengths and limitations to each source that need to be evaluated (Table 3.2) (2, 5).

Drawing upon a combination of these complementary tools can result in useful and rich information for mon-itoring and evaluation of the health workforce and its impact in health systems.

All countries collect at least some data on their popu-lation, mainly through periodic demographic censuses and household sample surveys that produce statistical information about people, their homes, their socio-economic conditions and other characteristics. Most censuses and labour force surveys ask for the occu-pation of the respondent (and other adult household members) along with other demographic characteris-tics, including age, sex and educational attainment.

Labour force surveys generally delve into greater details on, for example, place of work, industrial sector, remu-neration, time worked and secondary employment (6).

Many meaningful results pertinent to HRH analysis can be produced through tabulation of population-based data on labour activity. Other kinds of national house-hold surveys can also provide relevant information;

for example, surveys with questions on care-seeking behaviour have been used to help understand how fac-tors such as demographics, health insurance coverage and distance to a health facility influence not only cli-ents’ choice of whether or not to seek the services of a health-care provider, but also from whom services have been obtained (for example public or private sec-tor, formal or informal provider).

Health facility assessments can be conducted using different sampling approaches (establishment census or sample survey) and methodologies (self-admin-istered postal, fax or Internet-based questionnaire;

telephone or face-to-face interview). Depending on the nature of the data collection procedures and instru-ments, in-depth information can be obtained on health workforce metrics, for instance, in-service training and provider productivity. In addition, the nature of facility-based assessments facilitates the collection of data for numerous other indicators pertinent to health system performance assessment, such as infrastructure, avail-ability of supplies and costs (7).

In many countries, the computerization of administra-tive records – including public expenditure, staffing and payroll, work permits, trade union memberships and social security records – is greatly facilitating the

In many countries, the computerization of administra-tive records – including public expenditure, staffing and payroll, work permits, trade union memberships and social security records – is greatly facilitating the

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